Classification of building function using available sources of VGI
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/107684 https://doi.org/10.5194/isprs-archives-XLII-4-209-2018 |
Resumo: | This paper examines the feasibility of using data from OpenStreetMap (OSM), Facebook and Foursquare as a source of information on the function of buildings. Such information is rarely openly available and if available, would vary between cities by nomenclature, making comparisons between places difficult. Volunteered Geographic Information (VGI) including data from social media represents new potential sources of building function data that have not yet been exploited for this purpose. Using a part of the city of Milan as the study area, building data from OSM and points of interest (POIs) from OSM, Facebook and Foursquare were extracted to derive the building function. This resulted in the classification of building function for more than 80% of the buildings and demonstrated that both Facebook and Foursquare can complement the building function derived from OSM, helping to fill in missing gaps. This preliminary study has demonstrated the potential of this approach for deriving building function information from open data in a simple way yet still requires independent validation with alternative sources as well as extension to other areas that have different amounts of OSM and social media coverage. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Classification of building function using available sources of VGIVolunteered Geographic InformationOpenStreetMapFacebookFoursquareBuilding FunctionAutomated ClassificationThis paper examines the feasibility of using data from OpenStreetMap (OSM), Facebook and Foursquare as a source of information on the function of buildings. Such information is rarely openly available and if available, would vary between cities by nomenclature, making comparisons between places difficult. Volunteered Geographic Information (VGI) including data from social media represents new potential sources of building function data that have not yet been exploited for this purpose. Using a part of the city of Milan as the study area, building data from OSM and points of interest (POIs) from OSM, Facebook and Foursquare were extracted to derive the building function. This resulted in the classification of building function for more than 80% of the buildings and demonstrated that both Facebook and Foursquare can complement the building function derived from OSM, helping to fill in missing gaps. This preliminary study has demonstrated the potential of this approach for deriving building function information from open data in a simple way yet still requires independent validation with alternative sources as well as extension to other areas that have different amounts of OSM and social media coverage.International Society for Photogrammetry and Remote Sensing2018info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/107684http://hdl.handle.net/10316/107684https://doi.org/10.5194/isprs-archives-XLII-4-209-2018eng2194-9034Fonte, C. C.Minghini, M.Antoniou, V.Patriarca, J.See, L.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-27T08:16:01Zoai:estudogeral.uc.pt:10316/107684Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:24:00.401435Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Classification of building function using available sources of VGI |
title |
Classification of building function using available sources of VGI |
spellingShingle |
Classification of building function using available sources of VGI Fonte, C. C. Volunteered Geographic Information OpenStreetMap Foursquare Building Function Automated Classification |
title_short |
Classification of building function using available sources of VGI |
title_full |
Classification of building function using available sources of VGI |
title_fullStr |
Classification of building function using available sources of VGI |
title_full_unstemmed |
Classification of building function using available sources of VGI |
title_sort |
Classification of building function using available sources of VGI |
author |
Fonte, C. C. |
author_facet |
Fonte, C. C. Minghini, M. Antoniou, V. Patriarca, J. See, L. |
author_role |
author |
author2 |
Minghini, M. Antoniou, V. Patriarca, J. See, L. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Fonte, C. C. Minghini, M. Antoniou, V. Patriarca, J. See, L. |
dc.subject.por.fl_str_mv |
Volunteered Geographic Information OpenStreetMap Foursquare Building Function Automated Classification |
topic |
Volunteered Geographic Information OpenStreetMap Foursquare Building Function Automated Classification |
description |
This paper examines the feasibility of using data from OpenStreetMap (OSM), Facebook and Foursquare as a source of information on the function of buildings. Such information is rarely openly available and if available, would vary between cities by nomenclature, making comparisons between places difficult. Volunteered Geographic Information (VGI) including data from social media represents new potential sources of building function data that have not yet been exploited for this purpose. Using a part of the city of Milan as the study area, building data from OSM and points of interest (POIs) from OSM, Facebook and Foursquare were extracted to derive the building function. This resulted in the classification of building function for more than 80% of the buildings and demonstrated that both Facebook and Foursquare can complement the building function derived from OSM, helping to fill in missing gaps. This preliminary study has demonstrated the potential of this approach for deriving building function information from open data in a simple way yet still requires independent validation with alternative sources as well as extension to other areas that have different amounts of OSM and social media coverage. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/107684 http://hdl.handle.net/10316/107684 https://doi.org/10.5194/isprs-archives-XLII-4-209-2018 |
url |
http://hdl.handle.net/10316/107684 https://doi.org/10.5194/isprs-archives-XLII-4-209-2018 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2194-9034 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
International Society for Photogrammetry and Remote Sensing |
publisher.none.fl_str_mv |
International Society for Photogrammetry and Remote Sensing |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799134125865566208 |